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I use the svm function (for regression) to make forecast like I would with for exemple the arima function:
fit<-auto.arima(ts)
prediction<-forecast(fit,h=20)
which returns different attributes :

  1. prediction$mean which is the actual prediction
  2. prediction$lower and prediction$upper which are the boundaries of the confidence intervals on each points of the prediction$mean.

I would like the svm function (from e1071 package) to return a more detailed answer than just the value (like the forecast() would).
But I guess it is not implemented in the function yet. Is there another function to do it ? Or should I use bootstrap methods to try to estimate those boundaries? And if I should use this are they pre-implemented version of them instead of using sample over a for loop which is very time-consuming ?

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